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Chamber Dynamics and Clearing Farrokh Najmabadi, Rene Raffray, Mark Tillack (UCSD) Ahmed Hassanein (ANL) Laser-IFE Program Workshop February 6-7, 2001.

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Presentation on theme: "Chamber Dynamics and Clearing Farrokh Najmabadi, Rene Raffray, Mark Tillack (UCSD) Ahmed Hassanein (ANL) Laser-IFE Program Workshop February 6-7, 2001."— Presentation transcript:

1 Chamber Dynamics and Clearing Farrokh Najmabadi, Rene Raffray, Mark Tillack (UCSD) Ahmed Hassanein (ANL) Laser-IFE Program Workshop February 6-7, 2001 Naval Research Laboratory Electronic copy: http://aries.ucsd.edu/najmabadi/TALKS UCSD IFE Web Site: http://aries.ucsd.edu/IFE

2  Statement of Work: Initiate development of a fully integrated computer code to model and study chamber dynamic and clearing. Deliver the core of the code including the input/output interfaces, the geometry definition and the numerical solution control for multi-species (multi-fluid), 2-D transient compressible Navier Stokes equations. Provide chamber wall-interaction modules, which include physics of melting; evaporation and sublimation; sputtering; macroscopic erosion; and condensation and redeposition. Scope the range of chamber dynamics and clearing experiments that can be carried out in a facility producing 100-10,000 J of X-ray.  Deliverables: The core of the code including the input/output interfaces, the geometry definition and the numerical solution control, and 2-D hydrodynamics module: Oct. 1, 2001 Implementation of various physics modules: Jan. 31, 2002 Experimental plans: Jan. 31, 2002  Budget: Code development: (190k UCSD, 175k ANL), Experiment planning (75k UCSD) Statement of Purpose and Deliverables

3  The rep-rate is limited by the time it takes for the chamber environment to return to a sufficiently quiescent and clean, low-pressure state following a target explosion to allow a second shot to be initiated (goal: 100-200 ms). Understanding Chamber Dynamics and Clearing is a Critical R&D Item Gas dynamics: Compressible Radiation heat transport Dissipative processes … Volume interactions: In-flight evaporation In-flight re-condensation Chemistry … Surface Physics: Melting & melt layer behavior Evaporation/sublimation Sputtering Macroscopic erosion Condensation and redeposition …  Many complex phenomena should be understood and modeled.

4  “First pass” of target-released energy through the chamber – “fast” time scale (ns to several  s). Propagation of X-rays and ions through the chamber; Re-radiation of the ions & X-ray energy deposited in the chamber gas. At the completion of this phase, chamber volume is in a non- equilibrium state and material is released from the wall.  Relaxation of chamber environment to a equilibrium state – “slow” time scale (several  s to hundreds of ms). Mass and heat transport in the chamber & to/form chamber wall Relaxation to “residual” chamber environment (“pre-shot” environment) The “pre-shot” environment affects target injection & tracking, laser propagation, … Response of Chamber to Target Explosion Covers Two Vastly Different Time Scales

5 1-D Codes such as Bucky & Ablator Experiments such as shots on Z Codes such as TSUNAMI (2-D) and DSMC (3-D) Previous research is mainly for thick liquid walls “Fast” time-scale processes “Slow” time-scale: processes Non-Equilibrium Environment “Pre-shot” Chamber Environment Target injection, Laser propagation, …

6  TSUNAMI (UC Berkeley) : 2-D gas-dynamic equations with no viscosity, no heat conduction (not important), no radiation heat transport, Relatively simple wall boundary conditions: p=saturated vapor pressure, u=0, and n derived from EOS in the outer cell, Mainly exercised for thick liquid wall concepts, Used to model solid wall chambers as Master thesis by one our students.  DSMC* (NASA): DSMC solves Boltzman’s equation via Monte Carlo Method Used by ILE researchers to model KOYO chamber (wetted wall concept) Results were compared with TSUNAMI models * http://abweb.larc.nasa.gov:8080/~wilmoth/dsmc.html TSUNAMI & DSMC Codes Have Been Used for Chamber Clearing Modeling

7  Literature survey of work with TSUNAMI & DSMC indicates: It is essential to include proper initial condition (energy distribution in the chamber) and boundary conditions (wall interaction). Most of the work, however, used simple models and approximations for initial and boundary conditions. It is essential to include multi-dimensional effects (UCB, ILE, UCSD work). Need to include viscosity (ILE, UCSD work) and radiation transport.  Large body of work in the past 10 years on Computational Fluid Dynamics: relevant to chamber dynamics & clearing: Flame front propagation and combustion, Aerospace plane, … Most large scale codes use variation of CGF algorithm with adaptive mesh techniques.  Simulation experiments to benchmark calculations and validate physics models are essential. Review of Previous Work

8  Stage 1: Code infrastructure: module definitions and interfaces, I/O, geometry definition, Transient compressible Navier Stokes solver (most tests on simple 2-D geometries) including dissipative effects, Simple model for radiation transport, Use results from BUCKY as initial condition, Develop detailed wall-interaction modules (boundary conditions).  Stage 2: Adaptive mesh routines, most tests with simple and/or complex 2-D shapes. Detailed radiation transport model, New physics modules based on stage 1 code results and experiments  Stage 3: Tuning the code for complex 3-D geometries New physics modules based on stage 2 code results and experiments Chamber Dynamics and Clearing Code Development Is Broken Into Three Stages This year proposal

9 Stage-1 code Stage-2 codeExperiments Breakdown of Chamber Clearing Research Application: Experiment planning Design study support Stage 2 Code development Core development Wall-interaction modules Validation & Module Integration Doc. Documentation & release of the code Validation & Module Integration Adaptive Mesh routines Doc. App. Experiment planning Experiment Design Experiment Implementation 1 st year2 nd year Radiation transport

10  Transient compressible Navier Stokes solver: CFG algorithm-based numerical routines.  Mesh construction routines: Map simple 2-D physical domain(s) with regular boundaries (e.g., cylinders) into rectangular logical meshes. Gross mesh adaptation routines will be tested and implemented in stage 1.  Radiation transport: Simple radiation transport model based on implicit time stepping.  Wall-interaction modules (led by ANL): Melting & melt-layer behavior Evaporation & sublimation Sputtering Macroscopic erosion Condensation & redeposition  Module definition & interfaces (C++) Components of Stage 1 Chamber Dynamics and Clearing Code

11 Chamber Dynamics Simulation Experiment – Exploration and Planning  Simulation experiments are essential to Benchmark simulation codes; Ensure all relevant physical phenomena is taken into account  Relatively new field. Previous experimental work focused on shock propagation and/or condensation of wetted chamber walls.  Eventually, we need scaled experiments to screen concepts for implementation on IRE.  Two major areas should be investigated first: 1.A source of energy to produce prototypical environment for experimentation, 2.Experiment characterization and array of diagnostics.

12 Scaled Simulation Experiments can Help Address Many Chamber Issues 100–500 J Large-volume tests for geometrically prototypical testing 1–10 kJ Integrated (simultaneous) surface and volume effects Chamber dynamics in limited volume (~1 liter) 1–10 J Beam propagation and focusing Near-surface physics Diagnostic development and experimental techniques >10 MJ Integrated prototypical chamber testing Incl. neutrons Possible clean sources of energy include lasers and plasma focus

13 Chamber Dynamics Simulation Experiment – Experimental Characterization and Diagnostics  Chamber responses include transient temperatures, pressures, mass composition and physical forms in the chamber volume.  Three distinct time scales: Target yield and instantaneous surface response (~ ns time scale), Gas-dynamics (10-100  s), Thermal recovery (1-100 ms).  For example, possible methods for temperature measurement: Fast time scale: optical spectroscopy? Gas dynamics & thermal recovery: high-temperature thermal sensors located directly in the medium? Chamber wall temperature: IR camera?

14  Such a predictive capability requires: Computer simulation of increasing sophistication; Simulation experiments to bench mark the core and ensure that all relevant phenomena are taken into account.  Our Approach: Problem is complex and includes diverse phenomena. A joint proposal from UCSD and ANL to initiate the activity. We encourage and welcome collaborations. Utilize expertise in CFD community, import best numerical algorithms and focus on understanding phenomena relevant to high-average power laser chambers. Staged approach to code development and experiment planning: Clear deliverables at each stage and simulation/experiments progress sets development priorities for next stages. Long-term goal of this proposal is to develop a predictive capability for chamber dynamics and clearing (available for IRE)


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